Evidence map›Paper›PMID 33127901›Full record

ArticleNPJ biofilms and microbiomes2020

Strong oral plaque microbiome signatures for dental implant diseases identified by strain-resolution metagenomics.

Paolo Ghensi, Paolo Manghi, Moreno Zolfo, Federica Armanini, Edoardo Pasolli, Mattia Bolzan, Alberto Bertelle, Federico Dell'Acqua, Ester Dellasega, Romina Waldner and 3 more

Abstract read
In one paragraph

Article in NPJ biofilms and microbiomes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
79citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

79 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Gut microbes · 2025
    Article
  15. MedComm · 2025
    Review
  16. Biofilm development ofMicrobiology spectrum · 2025
    Article
  17. Article
  18. Article
  19. Article
  20. Article

19 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Paolo GhensiDepartment CIBIO, University of Trento, Trento, Italy.ORCID 0000-0002-8444-0489
Paolo ManghiDepartment CIBIO, University of Trento, Trento, Italy.
Moreno ZolfoDepartment CIBIO, University of Trento, Trento, Italy.ORCID 0000-0001-6661-4046
Federica ArmaniniDepartment CIBIO, University of Trento, Trento, Italy.
Edoardo PasolliDepartment CIBIO, University of Trento, Trento, Italy.
Mattia BolzanDepartment CIBIO, University of Trento, Trento, Italy.
Alberto BertellePrivate Practice, Trentino-Alto Adige, Italy.
Federico Dell'AcquaPrivate Practice, Trentino-Alto Adige, Italy.
Ester DellasegaPrivate Practice, Trentino-Alto Adige, Italy.
Romina WaldnerPrivate Practice, Trentino-Alto Adige, Italy.
Francesco TessaroloDepartment of Industrial Engineering, University of Trento, Trento, Italy.
Cristiano TomasiDepartment of Periodontology, Institute of Odontology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Nicola SegataDepartment CIBIO, University of Trento, Trento, Italy. nicola.segata@unitn.it.ORCID 0000-0002-1583-5794

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dental implants are installed in an increasing number of patients. Mucositis and peri-implantitis are common microbial-biofilm-associated diseases affecting the tissues that surround the dental implant and are a major medical and socioeconomic burden. By metagenomic sequencing of the plaque microbiome in different peri-implant health and disease conditions (113 samples from 72 individuals), we found microbial signatures for peri-implantitis and mucositis and defined the peri-implantitis-related complex (PiRC) composed by the 7 most discriminative bacteria. The peri-implantitis microbiome is site specific as contralateral healthy sites resembled more the microbiome of healthy implants, while mucositis was specifically enriched for Fusobacterium nucleatum acting as a keystone colonizer. Microbiome-based machine learning showed high diagnostic and prognostic power for peri-implant diseases and strain-level profiling identified a previously uncharacterized subspecies of F. nucleatum to be particularly associated with disease. Altogether, we associated the plaque microbiome with peri-implant diseases and identified microbial signatures of disease severity.

Indexed as

AdultAgedAged, 80 and overBacteriaCase-Control StudiesDental ImplantsDNA, BacterialFemaleHigh-Throughput Nucleotide SequencingHumansMachine LearningMaleMetagenomicsMiddle AgedPeri-ImplantitisPhylogenyDental ImplantsDNA, Bacterial

Identifiers

PMID33127901
PMCPMC7603341

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.